Model-based analysis of rapid event-related functional near-infrared spectroscopy (NIRS) data: A parametric validation study

To validate the usefulness of a model-based analysis approach according to the general linear model (GLM) for functional near-infrared spectroscopy (fNIRS) data, a rapid event-related paradigm with an unpredictable stimulus sequence was applied to 15 healthy subjects. A parametric design was chosen wherein four differently graded contrasts of a flickering checkerboard were presented, allowing directed hypotheses about the rank order of the evoked hemodynamic response amplitudes. The results indicate the validity of amplitude estimation by three main findings (a) the GLM approach for fNIRS data is capable to identify human brain activation in the visual cortex with inter-stimulus intervals of 4–9 s (6.5 s average) whereas in non-visual areas no systematic activation was detectable; (b) the different contrast level intensities lead to the hypothesized rank order of the GLM amplitude parameters: visual cortex activation evoked by highest contrast>moderate contrast>lowest contrast>no stimulation; (c) analysis of null-events (no stimulation) did not produce any significant activation in the visual cortex or in other brain areas. We conclude that a model-based GLM approach delivers valid fNIRS amplitude estimations and enables the analysis of rapid event-related fNIRS data series, which is highly relevant in particular for cognitive fNIRS studies.